Sunday, March 10, 2019

Advance Fracturing Fluids Improve Well Economics

The oil and gas industry has witnessed a revolution in fluids technology for hydraulic fracturing. Starting in the mid 1980s, focused research led to major improvements in the performance of well stimulation fluids. Today, new additives and fluids are extending these capabilities and providing innovative solutions to nagging problems. The results are more efficient and cost-effective treatments for enhancing well production.

 Hydraulic fracturing is one of the oil and gas industry's most complex operations. This technique has been applied worldwide to increase well productivity for nearly 50 years. Fluids are pumped into a well at pressures and flow rates high enough to split the rock and create two opposing cracks extending up to 1000 ft [ 305 m] or more from either side of the borehole. Sand or ceramic particulates, called proppant, are carried by the fluid to pack the fracture, keeping it open once pumping stops and pressure decline.

What defines a successful fracture? It is one that: 

  • is created reliably and cost-effetively
  • provides maximum productivity enhancement 
  • is conductive and stable over time.  

The Rock, the mechanics and the Fluid

Historically, fracturing has been applied primarily to low-permeability- 0.1 to 10 md-  formations with the goal of producing narrow, conductive flow paths that penetrate deep into the reservoir. These less restrictive linear conduits replace radial flow regimes and yield a several-fold production increase. For large-scale treatments, as many as 40 pieces of specialized equipment, with a crew of 50 or more, are required to mix, blend and pump the fluid at more than 50 barrels per minute (bbl/min). Pumping may last eight hours with 1,000,000 gal of fluid and 2,000,000 to 4,000,000 lbm of propant placed in the fracture.

Until recently, treatments were performed almost exclusively on poor producing wells (often to make them economically viable). In the early 1990s, industry focus shifted to good producers and wells with potential for greater financial return. This, in turn, meant an increased emphasis on stimulating high-permeability formations.

The major constraint on production from such reservoirs is formation damage, frequently remedied by matrix acidizing treatments. But acidizing has limitations, and fracturing has found an important niche. The objective in highly permeable foormations is to create short, wide fractures to reach beyond the damage. This is often accomplished by having the proppant bridge, or screen out, at the end, or tip. of the fracture early in the treatment. This "tip screenout" technique is the opposite of what is desired in low-permeability formations  where the tips is ideally the last area to be packed.

 Why the different approach? The answer is found in the relationship between fracture length and the permeability contrast between the fracture and the formation. Where the contrast is large, as for low-permeability reservoirs, longer fractures provide proportionally greater productivity. Where the contrast is small, as in high-permeability formations, greater fracture length provides minimal improvement. Fracture conductivity is, however, directly related to fracture width. Using short- about 100-ft [30 m] - and wide fractures can prove beneficial.

High-permeability formation treatments are on a far reduced scale. Only a few pieces of blending and pumping equipment are required, and pumping times are typically less than one hour, and often only 15 minutes. Fluid is pumped at 15 to 20 bbl/min with a total volume of 10,000 to 20,000 gal and total proppant weight of about 100,000 lbm. This technique has been successful in the North Sea, Middle East, Indonesia, Canada and Alaska, USA.

While fracturing treatments vary widely in scale, each requires the successful integration of many disciplines and technologies, regardless of reservoir type. Rock mechanics experiments on cores, specialized injection testing and well logs provide dat on formation properties. Sophisticated computer software uses these data , along with fluid and well parameters, to simulate fracture initiation and propagation. These results and economic criteria define the optimum treatment design. Process-controlled mixing, blending and high-pressure pumping units execute the treatment. Monitoring and recording devices ensure fluid quality and provide permanent logs of job results. Engineers tracking the progress of the treatment use graphic displays that plot actual pumping parameters against design values to facilitate real-time decision making. Production simulators compare treatment results with expectations, providing valuable feedback for design of the next job.

Thursday, February 21, 2019

Low Resistivity Pay Zones

Evaluating low-resistivity pay requires interpreters to discard the notion that water saturations above 50% are not economic. Various tools and techniques have been developed to assess these frequently bypassed zones, but there are no shortcuts to arriving at the correct petrophysical answer. 

When Conrad and Marcel Schlumberger invented the technique of well logging, low-resistivity pay was, practically speaking, a contradiction in terms. Their pioneering research hinged on the principle that gas-or oil-filled rocks have a higher resistivity than water-filled rocks. Through the years, however, low-resistivity pay has become recognized as a worldwide phenomenon, occuring in basins from the North Sea and Indonesia to West Africa and Alaska. With low oil prices driving the reexploration of mature fields, methods of intepreting low-resistivity pay have proliferated. 

This article examines the causes of low-resistivity pay in sands, then explores the tools and techniques that have been developed to evaluate such zones. A case study shows how log/core integration helps pinpoint the causes of low-resistivity pay in the Gandhar field in India. 

 Generally, deep-resistivity logs in low-resistivity pay read 0.5 to 5 ohm-m. "Low contrast" is often used in conjunction with low resistivity, indicating a lack of resistivity contrast between sands and adjacent shales. Although not the focus of this article, low-contrast pay occurs mainly when formation waters are fresh or of low salinity. As a result, resisitivity values are not necessarily low, but there is little resistivity contrast between oil and water zones.

Becauses of its inherent conductivity, clay, and hence shale, is the primary cause of low-resistivity pay. How clay contributes to low-resistivity readings depends on the type, volume and distribution of clay in the formation.

Clay minerals have a substantial negative surface charge that causes log resistivity values to plummet. This negative surface charge - the result of substitution in the clay lattice of atoms with lower positive valence - attracts cations such as Na and K when the clay is dry. When the clay is immersed in water, cations are released, increasing the water conductivity.

The cation exchange capacity, or CEC, expressed in units of milliequivalent per 100 grams of dry clay, measures the ability of a clay to release cations. Clays with a high CE will have a greater impact on lowering resistivity than those with a low CE. For example, montmorillonite, also known as smectite, has a CEC of 80 to 150 meq/100 g whereas the CEC of kaolinite is only 3 to 15 meq/100g.

Clays are distributed in the formation three ways: 
  • laminar shales- shale layers between sand layers
  • dispersed clays- clays throughout the sand, coating the sand grains or filling the pore space between sand grains
  • Structural clays- clay grains or nodules in the formation matrix

Laminar shales form during deposition, interspersed in otherwise clean sands. In the Gulf Coast, USA, finely layered sandstone-shale intervals, or thin beds, make up about half the low-resistivity zones. Many logging tools lack the vertical resolution to resolve resistivity values for individual thin beds of sand and shale. Instead, the tools give an average resistivity measurement over the bedded sequence, lower in some zones, higher in others.  

Intervals with dispersed clays are formed during the deposition of individual clay particles or masses of clay. Dispersed clays can result from postdepositional processes, such as burrowing and diagenesis. The size difference between dispersed clay grains and framework grains allows the dispersed clay grains to line or fill the pore throats between framework grains. When clay coats the sand  grains, the irreducible water saturation of the formation increases, dramatically lowering resistivity values. If such zones are completed, however, water-free hydrocarbons can be produced.

Structural clay occur when framework grains and fragments of shale or claystone, with a grain size equal to or larger than the framework grains, are deposited simultaneously. Alternatively, in the case of selective replacement, diagenesis can transform framework grains, like feldspar into clay. Unlike dispersed clays, structural clays act as framework grains without altering reservoir properties. None of the pore space is occupied by clay.

Other causes of low-resistivity pay include small grain size and conductive minerals like pyrite. Small grain size can result in low resistivity values over an interval, despite uniform mineralogy and clay content. The increased surface area associated with finer grains holds more irreducible water, and as with clay-coated grains, the increasing water saturation reduces resistivity readings. Intervals of igneous and metamorphic rock fragments - all fine grained- mimic the log signature of clays, featuring high gamma ray, low resistivity and litte or no spontaneous potential (SP). Unlike thin beds, this type of low-resistivity pay can vary in thickness from milllimeters to hunderds of meters.

Finally, sands with more than 7% by volume of pyrite, which has a conductivity greater than or equal to that of formation water, also produce low-resistivity readings. This type of low-resistivity pay is considered rare. 

The challenge for interpreting low-resisitivity sands hinges on extracting the correct measurement of formation resistivity, estimating shaliness and then accurately deriving water saturation, typically obtained from some modification of Archie's law. Improved vertical resolution of logging tools and data processing techniques are helping to tackle thin beds. Nuclear magnetic resonance (NMR) logging shows promise for assessing irreducible water saturation associated with clays and reduced grain size. And because the most opportune time to measure resistivity occurs during drilling, when invasion effects are minimal, resistivity measurements at the drill bit also play an important role in diagnosing low-resistivity pay. 

Thin Beds

One obvious method for resolving the resistivity of thin beds is to develop logging tools with higher vertical resolution, deeper depth of investigation, or both. Two logging devices that have proved especially helpful in evaluating thin beds are the AIT Array Induction Imager Tool and the FMI Fullbore Formation MicroImager tool. The AIT tool uses eight induction-coil arrays operating at multiple frequencies to generate a family of five resistivity logs. The logs have median depths of investigation of 10,20,30,60 and 90 in. and vertical resolution of 1 ft, 2 ft and 4 ft. The FMI tool images the borehole with an array of 192 button sensors mounted on four pads and four flaps. It has a vertical resolution of 0.2 in. [ 5 mm ] .

Successive improvements in resolving  thin beds are strikingly visible in a series of logs made 33 years apart in adjacent wells in the South Texas Vicksburg formation. In 1960, induction/ short normal logs indicated 7 ft of net gas pay and only two beds with resistivity greater than 2 ohm-m. In 1993, a new well was drilled within 100 ft [30 m] of the original well and logged with conventional wireline tools. The induction/SFL Spherically Focused Resistivity logs doubled the estimated pay to 14 ft [4.3 m], with seven beds above 2 ohm-m. Later the same year, the second well was logged with a combination of AIT and IPL Integrated Porosity Lithology tools. The high resolution of the AIT tool - 1 ft versus 2 ft for the induction- and the enhanced sensitivity of the IPL-derived neutron porosity increased net pay to 63 ft [19.2 m] and showed 13 beds with resistivity greater than 2 ohm-m.

Resistivity Measurements at the Bit

Improvements in mesurements-while-drilling (MWD) technology have not only boosted the efficiency of directional drilling, but also enhanced thin-bed evaluation. Two tools, the RAB Resistivity-At-the-Bit tool and the ARC5 Array Resistivity Compensated tool - are especially useful in thin-bed environments by providing resistivity data before invasion has altered the formation.

The RAB tool provides five different resistivity readings plus gamma ray, shock and tool inclination measurements. Configured as a stabilizer or a slick collar, the RAB tool is run behind the bit in a rotary drilling assembly and above the motor in a steerable drilling assembly.

One resistivity measurement, called "bit resistivity" , uses the drill bit as part of the transmitting electrode. With the RAB tool attached to the bit, alternating current is circulated through the collar, bit and formation before returning to the drillpipe and drill collar above the transmitter. In the case of oil-base mud, which is an insulator, the current loop is complete only when the collars and stabilizers touch the borehole wall. The vertical resolution of the RAB bit resistivity is only 2 ft and it gives the earliest possible warning of changes in formation resistivity.

Four additional resistivity measurements, with 1-in. vertical resolution for thin-bed applications, are made with three button electrodes and a ring electrode. The shallow depths of investigation- 3, 6 and 9 in. for the buttons and 12 in. for the ring electrode- allow interpreters to characterize early-time invasion.

The recently-introduced ARC5 tool provides five phase and attenuation resistivity measurements, like the AIT tool, with a vertical resolution of 2 ft. With a 4 3/4 in. diameter, it is especially useful for formation evaluation in slim holes typical of deviated drilling. 

 The measurements and spacings of the ARC5 and AIT tools are comparable, although not identical, making petrophysical evaluation with either tool in the same well or between wells seamless. The multiple measurements of the ARC5 tool also allow interpreters to radially map out the invasion process. The additional phase and attenuation measurements provide a better characterization of electrical anisotropy than existing MWD tools.

Improving Thin-Bed Evaluation Through Data Processing

Despite the emphasis on developing high-resolution resistivity logging tools, many openhole tools still have a vertical resolution of 2 to 8 ft [ 0.6 to 2.4 m] . Several data processing techniques have been developed to enhance the vertical resolution of these traditional tools. All methods use at least one high-resolution measurement to sharpen a low-resolution measurement to sharpen a low-resolution one and require a strong correlation between the two. 

SHARP analysis relies on high-resolution inputs, such as Formation MicroScanner, FMI, or EPT Electromagnetic Propagation Tool logs to define a layered model of the formation. The program looks at the zero crossings on the second derivative of the high-resolution log, where the slope changes sign, to indicate bed boundaries. In the case of a Formation MicroScanner or FMI log, the SHARP program examines the second derivative of an average resistivity reading from all button sensors.

With bed boundaries established, SHARP analysis plots a histogram of the frequency of a particular resistivity value within the logged interval of interest. By styudying how resistivity values cluster an interpreter can group the values into different populations, or modes. 

In addition, SHARP evaluation assumes that petrophysical parameters such as density, neutron porosity and sonic velocity are also constant in a given mode.

When the synthetic and measured logs match, the model can be used as a high-resolution input into the ELAN interpretation. To sharpen the resolution of other logs, such as the gamma ray, the model of bed boundaries determined previously is utilized to reconstruct other squared, enhanced logs for high-resolution formation evaluation. 

Working with logs from the GLT Geochemical Logging Tool, researchers picked a high-resolution clay indicator, either the FMI or EPT log, and calibrated it to the clay volume derived from the  GLT measurement. In addition to clay volume, the GLT tool combines nuclear spectrometry logging measurements to determine mineral concentrations and cation exchange capacity of the formation.

Using Electrical Anisotropy to Find Thin-Bed Pay

James Klein and Paul Martin of ARCO Exploration and Production Technology in Plano, Texas, and David Allen of Schlumberger Wireline & Testing in Sugar Land, Texas are modeling electrical anisotropy to detect low-resistivity, low-contrast pay such as thin beds. The researchers found that a water-wet formation with large variability in grain size is highly anisotropic in the oil leg and isotropic in the water leg. They attribute the resistivity anisotropy to grain-size variations, which affect irreducible water saturation, between the laminations. 

They tested their theory by modeling the thin, interbedded sandstones, siltstones and mudstones of the Kuparuk River formation A-sands of Alaska's North Slope, located 10 miles [16 km] west of Prudhoe Bay. The model, based on a Formation MicroScanner interpretation , contains layers of low-permeability mudstone and layers of permeable sandstone with variable clay content.

The tested their theory by modeling the thin, interbedded sandstones , siltstones and mudstones of the Kuparuk River formation A-sands of Alaska's North Slope , located 10 miles [ 16 km] west of Prudhoe Bay. The model, based on Formation MicroScanner interpretation, contains layers of low-permeability mudstone and layers of permeable sandstone with variable clay content.  

The simulated resistivity data are described as either perpendicular - measured with current flowing perpendicular to the bedding - or parallel- measured with current flowing parallel to the bedding.

Plotting perpendicular versus parallel resistivity for a given interval shows how hydrocarbon saturation influences electric anisotropy. Simulated resistivity data in the oil column curve to the right, but simulated resistivity data in the water leg are nearly linear. The position of data along the oil column indicates the lithology of the formation.

Today, this technique works only with 2-MHz MWD tools such as the CDR Compensated Dual Resistivity tool. The CDR phase and attenuation measurements provide a unique response to anisotropy that allows the perpendicular and parallel resistivities to be determined. The technique requires that the logging tool be parallel to the beds so that differences in the phase and attenuation of resistivity measurements can be used to establish anisotropy. Although the technique cannot yet be applied at other angles, its originators believe some operators will value it enough to tailor the deviation of their wells so that logging tools can run parallel to beds of interest.

Nuclear Magnetic Resonance Logging

Although thin-bed evaluation is challenging, the tools and techniques described so far provide answers in most cases. More troublesome to interpreters than thin beds is another prominent cause of low-resistivity pay, reduced grain size, which contributes to high irreducible water saturations. The CMR Combinable Magnetic Resonance tool shows potential for measuring irreducible water saturation and pore size.

The CMR tool looks at the behavior of hydrogen nuclei-protons-in the presence of a static magnetic field and a pulsed radio frequency (RF) signal. A proton's magnetic moment tends to align with the static field. Over time, the magnetic field gives rise to a net magnetization- more protons aligned in the direction of the applied field than in any other direction.

Applying an RF pulse of the right frequency, amplitude and duration can rotate the net magnetization 90 degree from the static field direction. When the RF pulse is removed, the protons precess in the static magnetic field, emitting a radio signal until they return to their original state. Because the signal strength increases with the number of mobile protons, which increases with fluid content, the signal strength is proportional to the fluid content of the rock. How quickly the signal decays- the relaxation time- gives information about pore sizes and , to some extent, the amount and type of oil.

A CMR log displays distributions of relaxation, or T2 times, which correspond to pore size distributions. The area under a spectrum of T2 times is called CMR porosity.

Unlike previous NMR tools, the CMR tool is a pad-mounted device. Permanent magnets in the tool provide a static magnetic field focused into the formation. The CMR tool's depth of investigation , about 1 inch [ 2.5 cm] , avoids most effects from mudcake or rugosity. Its vertical resolution of 6 inch [15 cm] allows for comparison with high-resolution logs.

A low-resistivity example from  the Delaware formation in West Texas shows how the NMR response allows log interpreters to measure residual oil saturation directly from the CMR log. NMR measurements on core samples from the Delaware formation show that the NMR response will decay within the first 200 milliseconds (msec) if the pores are filled with water. If the pores are filled with oil, however, the signal decays after about 400 msec. 

The T2 distributions in track 4 have been divided into three parts. The area under the T2 curve to the left of the first cutoff, shown as a blue line at 33 msec, represents irreducible water saturation. The area under the curve from 33 msec to 210 msec (red line) represents producible fluid. Above 210 msec, the area under the curve represents oil, presented as a CMR oil show in track 3. This measurement of oil actually refers to residual oil saturation since the CMR tool looks only at the flushed zone.

Thursday, January 31, 2019

Classic Interpretation Problems: Evaluating Carbonates

In recent years, there has been a small revolution in our ability to evaluate carbonates. Novel technology and a community of interpreters determined to crack one hard nut are forcing carbonate reservoirs to reveal many of their secrets.

 Carbonate reservoirs account for 40% of today's hydrocarbon production, and because of several elephant fields in the Middle East they are expected to dominate production through the next century. Therefore, understanding carbonate reservors and producing them efficiently have become industry priorities and are likely to remain so. 

Current efforts in carbonate exploitation focus on correctly targeting new wells,  frequently horizontal, to optimize production from untouched reserves and on ensuring that massive water injection schmes deliver an effective sweep of the reservoir.  In support of these efforts, geoscientists are trying to decipher the enigma of carbonate rock's complex pore space and understand how permeability barriers and conduits affect reservoir behavior.  This article tracks the interpretation process,from carbonate rock description and petrophysical log evaluation to new techniques for measuring permeability downhole and mapping large-scale flow conduits and barriers. 

Carbonates for Beginners

Carbonates and sand-shale rocks, or siliciclastics, are worlds aparts. Whereas silicicalstic rocks are composed of a variety of silica-based grains that may have traveled hundreds of miles from their source, carbonate rocks mainly consists of just two minerals- calcite and dolomite- and remain near their point of origin. Carbonates form in shallow and deep marine settings, evaporitic basins, lakes, and windy desserts. Most of the carbonates formed in the past have shallow marine origins, but the most widespread type of modern carbonate is formed in deep water. Silica-based rocks generally stand up to the rigors of geologic time, undergoing only minor alteration, or diagenesis. Their depositional record is preserved, with bedding planes on outcrops and subsurface correlations between wells clearly recognizable. The grains are regularly shaped, and the pore space, though complicated, remains intergranular. 

Carbonate rocks, on the other hand, are chemically unstable and undergo substantial alteration such as mineral dissolution and dolomitization - the replacement of calcium carbonate by magnesium carbonate. Carbonates house a jumble of complex particles, including a huge variety of biological origin, and an even more complex pore space. This complicates the tracking of facies across a carbonate reservoir and the assessment of the productivity of a given carbonate formation.

The typical carbonate rock is made of grains, matrix and cement. Grains are either skeletal fragments of small organisms or particles precipitated from calcium-rich water. The latter includes a variety of small, accretionary grains identified according to their size, origin and internal structure.

Matrix is the lithified mud of deposition that fills most of the space not occupied by grains. In carbonates, fine mud has several sources- chemical precipitation, breaking of skeletal material into finer material,  remains of algae, and others. On lithification, mud becomes a very fine-grained calcite called micrite. 

Cement describes cyrstalline material that forms in most of the space remaining between grains and matrix or between grains themselves, binding them. Cement may have a variety of crystal sizes depending on its composition, the conditions of crystallization and the spaces to be filled.

Crucial to the interpretation of carbonates is classifying the numerous ways grains and matrix coexist. Progress in categorizing these complexities surged in the late 1950s because of pressure within oil companies to better understand their carbonate assets. The classification that has stood the test of time most successfully is by Robert Dunham.

Dunham classifies a spectrum of rock types based on the internal structure and texture of the rock. Mudstone consists mainly of matrix in which relatively few grains are suspended. Wackestone is also matrix-supported but has more grains. Packstone has enough grains for them to start providing support - matrix fills the remaining nonpore space. Grainstone has plenty of grains providing  support and includes progressively less matrix. Finally , boundstone describes carbonate rocks in which the original material provided support during deposition, such as in reefs. Cyrstalline describes rock that has lost its depositional fabric because of diagenetic recrystallization , for example, dolomitization.

Dunham's classification provides some clue to the energy of deposition. The mud-based mustone and wackestone are deposited in low-energy settings. Packstone and grainstone would appear to be from high-energy deposition, but given significant diagenesis, these grain-supported rocks could equally well have been deposited as mud-supported agglomerations and then through compaction and chemical alteration transformed to their present state. The difficulty in classifying carbonates to reflect both their current state and depositional history demostrates how dominant diagenesis is in forming the final carbonate rock.

Diagenesis may be divided into five main mechanisms : compaction- the reduction of pore space in response to tighter grain packing as overburden increases; carbonate degradation- the destruction of carbonate material through chemical dissolution and micritization, the transformation of large crystal into small ones; carbonate aggradation- the construction of carbonate material through precipitation of cement between grains, and recrystallization, such as the replacement of limestone by dolomite; stylolitization - the formation of stylolites, irrregular planes of discontinuity between rock units due to compaction-related pressure solution; and fracturing- the planar breaking up of rock mass due to stress.

Time and diagenesis generally work against the preservation of porosity. Young carbonates usually have porosities around 60%. Old carbonates have just a percent or two.  Reservoir carbonates survive with porosities of 5 to 15% largely because the presence of hydrocarbon impedes further destruction of porosity. The typically prolonged and extensive diagenesis in carbonates also usually obscures the provenance and history of the rock.

Reservoir Description

How does the reservoir geologist use these descriptions to help plan the optimum exploitation of a carbonate reservoir? Identifying and classifying carbonates are crucial in two key tasks. First, assessment of the reservoir's paleoenvironment builds a broad understanding of likely reservoir geometry. Then, detailed well-to-well correlation of lithofacies helps contruct a detailed three-dimensional picture. 

Clues to paleoenvironment come from every available source- seismic surveys, outcrop studies, cuttings and core analysis, and logs, including those from the latest generation of electrical imaging tools, which can capture the wellbore likeness to a resolution of about 5 mm. The main paleoenvironment indicators are:

  •  Lithology - This provides a general idea of the depositional setting. The presence of clastic rocks indicates an external source of sediment, while their absence indicates an environment free of external influence.
  • Rock texture- The Dunham classification of texture provides some idea of the energy deposition. Grain size variations also point to the sequence of deposition. For example, a fining upward sequence may indicate a relative sea level rise, or marine transgression. A coarsening upward sequence probably indicates a relative sea level drop. 
  • Sedimentary structure - Large-scale sedimentary structures are more difficult to see in carbonates than in siliciclastics, but when identified, they offer powerful clues to the depositional environment. Examples are cross beds in eolian dunes or solution grooves caused by irregular dissolution of the surface of a carbonate rock.
  • Biofacies - Identification of the wide variety of skeletal grains, burrows and molds may pinpoint precise geological time and settings. Ages and habitats of hundreds of carbonate creatures have been tabulated for this purpose.
  • Nonskeletal content - Grains formed by precipitation and accretion provide a powerful indicator of depositional setting. For example, homogeneous pallets develop in quiet lagoons, while concentrically layered ooids occur mainly in active, shallow environments. 
  • Authigenic minerals- The cement and minerals that form in the rock after deposition provide some additional clues. The presence of pyrite suggests reducing (deoxidizing) conditions; glauconite indicates marine conditions; organic matter indicates little reworking.

Slowly evidence accumulates, and the origin and evolution of the reservoir become less conjectured and more certain. In comparison, the mapping of lithofacies is a detailed, nuts-and-bolts task, but no less challenging. Unlike silciclastics, carbonates usually carry no bedding signatures that allow read well-to-well correlation across a field. Even dipmeter correlations across the borehole can be elusive. There are exceptions. Eolian carbonate deposits, for example, display continuity and bedding signatures exactly like their siliciclastic equivalents. More freqently, though, carbonates exhibit a mix of features such as fractures, breccia, stylolites and vugs.

Helping the reservoir geologist recognize and catalog these features in wells drilled with water-base mud is the FMI Fullbore Formation MicroImager tool, which provides a picture of most of the borehole with 192 small current-emtting buttons mounted on four pads and four flaps. In the images, light color denotes high resistivity, indicating rock grains or hydrocarbon-filled pores, and dark color indicates low resisitivity such as water-filled pores or shale.The images are no subtitue for core analysis, but rather a complement to them. Other evidence is frequently needed to corroborate an interpretation, for example to decide whether a dark patch is porosity or shale. However, an experienced interpreter of FMI images can glean strong evidence of numerous types of carbonate features down to the centimer scale.

A recent trend in FMI interpretation has been toward quantitative analysis of the images. One processing method automatically extract five facies types based on a textural classification by Nurmi et al. The facies are uniform zones of constant conductivity or resistivity, layered zones of alternating conductive and resistive layers; zones  with interwoven or contiguos conductive areas, interpreted as interconnected porosity; resistive zones with isolated conductive areas, intepreted as nonconnected pores; and conductive zones with isolated resistive areas, caused for example by nonconducting calcite or anhydrite nodules. Such a zonation can be rapidly calculated from the images and lends itself readily to facies mapping across a field.

A more advanced processing method actually delineates identifiable objects such as rock grains or pores on the images. This is quite a challenge because picking the edge of an object depends somewhat on overall image intensity , which varies. The solution is to equate object boundaries with inflection point in image intensity. This approach is incorporated in SPOT - Secondary Porosity Typing - prototype software running on GeoQuest Geoframe platform. 

Current SPOT processing can yield the boundaries of both resistive (light color) and conductive (dark color) features. In tests made on laboratory rock samples bored with "pores" of varying but precisely known diameter, the processing has given an accurate and consistent pore delineation.

Once resistive and conductive features are delineated , then all manner of quantitative information can be computed, such as their average size , the spatial density of the features, the total area on the image covered by the features, and the degree to which like features are connected. We will later address how these new parameters may contribute to understanding of rock porosity and permebility.

The average sizes of resistive and conductive features have recently been used to help identify Dunham rock types in Occidental Oil Company field in Indonesia and thus contribute to facies mapping. In this interpretation, resistive features correspond to carbonate coral framework or grains, while conductive features correspond to pores or micritic matrix. On a log, the average sizes of the two types of features are played back together. The interpretation proceeds by noting the separation between the curves and also their absolute magnitudes.

Mudstone is interpreted when separation is at a maximum. This occurs when the average size of conductive features peaks- that is, micritic cement dominates- and the average size of resistive features - or grains - drops.

Wackestone is interpreted when the average size of resistive features increases, while the average size of conductive features reamins about the same. Packstone is interpreted when of resistive features peaks. And finally, grainstone is interpreted when the sizes of conductive and resistive features become equal. This broad-brush methodology has been verified against microfacies descriptions from cores in two wells in the field. Furthermore, the frequency with which the two curves mirror one another appears to indicate the frequency of a complete depositional cycle- from low-energy mudstone to high-energy grainstone.

Without images, mapping facies following gamma ray and other log signatures can often prove unreliable. The safest bet, short of coring every borehole, is to collectively interpret all available log data, initially calibrating the interpretation results to core data. An example of this approach can be found in a study by the Indian Oil and Natural Gas Commision (ONGC) that recently addressed a complex Middle Eocene Carbonate formation in offshore India.

In this study, the first step was to identify facies in the four cored wells according to Dunham's classification. This required the analysis of 120 thin sections, 12 polished sections and 6 scanning electron microscope images. This petrologic interpretation was then integrated statistically with five log measurements made in the same wells - density, neutron porosity, sonic travel time, gamma ray and saturation. Matching the log measurements to the facies descriptions revealed clear links between weighted combinations of log data and the Dunham classification. However, rather than Dunham's four, the logs recognized five facies types,  the last of which always occured within a wackestone zone but at depths where no core was retrieved. This facies was termed wackestone. With logs calibrated to a core facies description, a facies interpretation could be made directly from logs in all the remaining uncored wells, and the facies mapped between wells. 

Petrophysical Evaluation

Facies determination from logs is hard enough, but the challenge of establishing petrophysical parameters such as saturation and permeability is even more daunting. The reason lies squarely with the complex diagenesis and resulting convoluted pore systems of most carbonate rocks. Log analysts divide porosity into primary and secondary appearing as the rock matures and diagnesis prevails. 

The variety in pore type explains why permeability answers remain so elusive. Vugs and their cousins may make for high porosity , but a consistent pore connectivity, usually taken for granted in sandstones, may or may not be present. Worse yet, the chaos reigns at all scales. In sandstones, small 1/2 inch. plugs bored from cores usually provide samples homogeneous enough for estimating average permeability. In carbonates, however, sometimes not even a whole piece of core can be regarded as representative. The discepancy between permeabilities measured at different scales may be relatied to heterogeneity or to anisotropy. The only sure way of estimating reservoir-scale permeability is by using wireline, drillstem or production tests. This was the approach taken in the second phase of the Indian study, in which nine well tests in two wells established a link between carbonate facies type and permeability.

Each carbonate facies type was allowed  a permeability value, to be determined. Then, for each test, the well's flow capacity calculated during the test was matched with the sum of the individual flow capacities of the wwell's various facies types. Each facies' flow capacity was the product of the facies type's unknown permeability and its cumulative thickness in the well. The result of the match was a range of permeabilities for each facies type, two types - grainstone and wackestone- being particulary permeable. Production logs in one well confirmed the productivity of wackestone. 

A much earlier study , predating imaging technology, also recognized clear differences in permeabilities of the rock types of the Dunham classification. This study first  used a rudimentary log interpretation method to distinguish one rock type from another .

 Once the type was identified, a relevant porosity-permeability relationship was applied at each depth to calculate permeability from porosity logs. The procedure resulted in far better agreement with core permeability measurements than had previously been obtained.


In general, there are two ways to establish elusive petrophysical parameters such as permeability from log data. One is to link the parameter statistically to log data , calibrating the link with measurements of the parameter made in the field or laboratory. The calibration can be in just one well or an entire field. An example is the Indian offshore study where well test results were linked to a statistically derived facies interpretation. The variety of such statistical methods is immense and currently extends to the use of neural networks that attempt to mimic and even improve on our inherent ability to recognize patterns in diverse data.

 The other approach is to somehow directly measure something about the rock's pore space, ideally from logs, and then tie this in with sought-after petrophysical parameters such as saturation and permeability. To this end, the newest measure comes from FMI images, again thanks to SPOT processing. The proportion of an image delineated as pore space leads directly to a new estimate of porosity, subject of course to the interpretation that dark areas of the image are indeed pores.

In a well drilled through a carbonate reservoir in Italy, SPOT-derived porosity compares well with porosity conventionally interpreted from neutron and density logs.

In much of the logged interval, the two porosites agree well, while elsewhere porosity derived from the FMI images is substantially less than conventional porosity. This could be due to the FMI tool responding only to pores larger than the 5-mm resolution of the tool and missing smaller intergranular and micritic pores. Interestingly, zones where the two porosities differ coincide with zones flagged with a secondary porosity index by the SPOT interpretation.

Another SPOT calculation is connectivity, an elaborately conceived but necessarily limited attempt to quantify the degree of connection between pores identified on images. A limitation is imposed because two-dimensional images can say only so much about three-dimensional connectivity. Nevertheless, SPOT connectivity has successfully predicted the productivity of oil and gas well in Texan and Oklahoman Ordovician carbonates with vuggy, connected porosity.

Without images, the commonest approach to pore geometry lies through consideration of Archie's law with its cementation exponent m: 

in which Rt, Rw and porosity are, respectively, the water-filled formation resistivity, connate water resistivity and porosity. Early on, researchers realized that the cementation exponent captured something about the pore space, particulary its tortuosity, and thus could serve to estimate permeability as well as interpret resistivity logs. Several theoretical expressions for permeabilities based on m have been developed, this being a recent example:

In which R is an "effective" pore radius in microns. 

The exponent m measures reasonably constant at about 2 for sandstones, as it does for similarly constructed oolitic carbonates. But otherwise in carbonate rock, it wanders all over. In fractured carbonate rock m tends to 1, and in rocks with nonconnecting vugs m rises to 3,4 or higher. A particularly copious study on Qatar carbonates by Focke and Munn shows not only how m varies with porosity- it varies a great deal- but also how that functionality depends on permeability. The challenge in using m to evaluate a carbonate therefore depends on being able to reliably estimate the exponent at any depth, rather than use an arbitrary value, generally 2, derived from observations on sandstones.

Guidelines for achieving this were first offered by Lucia of Shell Oil in 1981. Using samples from carbonate reservoirs in Texas, USA and Alberta, Canada, Lucia noted that m depended unambiguosly on the proportion of the rock's porosity coming from unconnected vugs.  Estimate that from core samples, he suggested, and a likely m could be derived for selected intervals in the well.

But a more versatile method was soon devised that permitted estimating m foot by foot. This made use of a new logging measurement- high frequency electromagnetic propagation travel time, or tpl. Like the resistivity log, tpl responds to water-filled porosity, but does so without an exponent. 

Combining resistivity and tpl therefore allows estimation of porosity for a continuous evaluation of m. The results of such an m computation transformed the accuracy of carbonate evaluation in a number of Middle East fields. The methodology was later extended to take advantage of yet another wireline masurement, the TDT Thermal Decay Time log, permitting the continuous evaluation of not just m, but also the saturation exponent n. 

The exponent n appears in Archie's law

 in which Sw is water saturation. Like the exponent m, n also runs into trouble in carbonates, sometimes varying dramatically from the conventionally assumed value of 2. This has been shown in several sets of experiment on cores. Petrophysicist suspect the likely cause of discrepancy is tiny micropores in the micritic matrix. Most probably, these small pores still contain original water while the larger pores contain oil. It is also probable that the micrite remains water wet, while the grains have become oil wet. Both phenomena would explain why carbonate formations producing only oil sometimes exhibit low resisitivities more characteric of a water-bearing formation. Essentially, the water-filled micropores provide a short-circuit to the survey current. 

New Logging Techniques 

 Today, two new techniques - nuclear magnetic resonance (NMR) logging and Stoneley wave logging- offer new perspectives on carbonate permeability and pore structure. The theoretical foundations for both techniques have been known for years, but until recently neither has received adequate tehnical implementation. That is changing with the introduction of the CMR Combinable Magnetic Resonance tool and the DSI Dipole Shear Sonic Imager tool.  

In nuclear magnetic resonance, sharp magnetic pulses are used to momentarily reorient hydrogen molecules away from the ambient magnetic field direction. After each pulse subsides, the hydrogen molecules realign themselves with the ambient field, oscillating about it as they do so. Observing these oscillations permits measuring how many hydrogen molecules relax after the imposed magnetic pulse and also the rate at which they realign to the ambient field, called the relaxation.

The implications for logging are dramatic. The measurement of how many hydrogen molecules relax provides a measure of porosity, and the relaxation times indicate the size of pores containing the hydrogen molecules. Relaxation times are short in small pores because the hydrogen molecules are near the grain surface where interaction with surface charges speeds relaxation. Relaxation times are longer in larger pores. Measuring the spectrum of relaxation times - so -called T2 relaxation the formation. This rules out the possibility of  a borehole signal, a problem that plague eariler technology that used instead the much weaker and unfocoused earth's field. Eliminating the borehole signal used to require the expensive and unpopular technique of doping the entire mud column with magnetite. The new tool's depth of investigation is about 1 inch [2.5 cm] , and a dead zone directly in front of the pad avoids most effects from mudcake or rugosity. Vertical resolution is just 6 inch [ 15 cm] , facilitating comparisons with the high-resolution FMI logs.

Recent CMR logs run in carbonate formations in West Texas coupled with laboratory measurements on cores from the wells illustrate exciting possibilities for overall petrophysical evaluation. The formations in question are partly dolomitized carbonates with a good deal of nonconnected vuggy porosity. In addition, silt layers create vertical permeability barriers. The main interpretation challenge is to estimate at any depth what percentage of porosity actually contributes to production. This requires being able to discount the minute pore space in the silt and also any vuggy porosity that is not connected.

T2 spectra were measured on water-saturated cores both before and after they had been centrifuged to expel all producible water. Before centrifuging, the spectra show water-filled porosity covering the full range of pore sizes, while spectra after centrifuging no longer show the large pore sizes, since the water has been expelled from them. Equating the porosity difference between the two spectra with the volume of water expelled during centrifuging established a T2 cutoff of 95 msec to divide large from small pores. Applying this cutoff to spectra measured by the CMR tool provided an estimate of small-pore porosity that correlated well with silt intrusions evaluated from other logs. Following visual analysis of the cores, a second cutoff at 750 msec was selected to isolate vugs from intergranular porosity. This was also applied to spectra measured downhole , providing a log of vuggy porosity. 

Recent laboratory work on core samples from the carbonate Mubarazz field in Abu Dhabi, UAE, confirms the potential of NMR measurements. 

A challenge in this area is to distinguish small micropores in the micrite matrix from the much larger productive intergranular pores. Analyzing 20 samples from two wells, a team of Schlumberger and Abu Dhabi Oil Company geoscientist found that micropores were correctly identified using a relaxation time cutoff of 190 msec on laboratory-measured T2 spectra. Furthermore, permeable grainstone facies could be distinguished from lower-permeability packstones and mudstones with a cutoff of 225 msec. Finally, the NMR data could be interpreted to give more accurate permeability estimates than those obtained from conventional porosity logs. The CMR logging tool is currently being tested in Abu Dhabi, and expectations are high that similarly impressive results will be obtained in boreholes.


Another logging tool, the DSI imager, gains direct entry to permeability by physically moving fluid through the formation. This is achieved when low-frequency tube waves- called Stonely waves- propagate up and down the borehole. The stonely wave preserves most of its energy in the borehole, but in permeable formations some energy is attenuated when wave pressure pushes fluid from the borehole into the formation,similar to a quick,small-scale well test. This slows the velocity of the wave by an amount that can be related to the ratio of formation permeability to fluid viscosity. Given a viscosity for the borehole fluid, in well-controlled circumstantes such as laboratory measurements or borehole with no mudcake, the permeability can then be estimated.

 The DSI tool generates Stonely waves with a special monopole transmitter at frequencies of 600 Hz to 5 kHz, ideal for tube-wave logging and a quantum leap ahead of previous technology equipped with transmitters operating in the 10 to 20 kHz range. Recent estimation of permeability using Stoneley-wave velocity as obtained from the DSI tool shows impressive agreement with core permeability measurements in an Abu Dhabi carbonate reservoir. 

The method of obtaining permeability using Stoneley-wave velocity requires knowing the formation's density and shear velocity. A second method establishes permeabilty from the Stoneley wave without other data. This method is based on observing how permeability attenuates Stonely wave energy by directly comparing signals from near and far receivers. Attenuation is greater at higher frequencies, so the comparison is more sensitive if measured at the high end of the Stoneley-wave frequency spectrum. Excellent agreement has been observed in Middle East carbonate reservoirs between permeability estimates obtained using this second method and production logs and core data. 

Research continues into improving Stonely-wave permeability, for example in accounting for the presence of mudcake, which almost certainly interferes with the tube wave's ability to move formation fluids.

Large-Scale Features

Mapping reservoirs at the large scale and understanding their complex petrophysics at the small scale are all part of the challenge facing reservoir geologists and engineers. But in carbonates, additional care must be taken to recognize and evaluate two types of medium to large scale features that are caused by overburden and tectonic stresses. Either can dramatically affect reservoir performance , creating heterogeneous or anisotropic behavior where none might otherwise be suspected. These two features are stylolites and fractures.

Stylolites occur in any sedimentary formation, but are particularly common in carbonates. Stylolites are easily recognized on outcrops and cores as irregular planes of discontinuity between rock units. Formed during compaction, probably through the mechanism of pressure solution, stylolites concentrate fine-grained insoluble residue along their  irregular seams. They are usually assumed to act as permeability barriers, but some core measurement results confirm that stylolites can develop permeability. Identifying them and evaluating their imact on permeability are therefore top priorities for the reservoir engineer.

Borehole imaging has greatly facilitated the identification  of stylolites downhole . Viewed with the FMI tool, they appear in three common varieties. First, some stylolites exhibit undulating but slightly irregular surfaces and are filled with dark, therefore conductive material, probably clay. A second group of sylolites seems to have an associated band of light color, most likely resistive calcite. The third type of sylolite clearly shows associated extensional fractures caused by excessive overburden stress.

The question remains: Which stylolites form permeability barriers and which do not? Until recently, there has been no sure way of deciding. Now, answers are obtainable from a third-generation wireline testing tool, the MDT Modular Formation Dynamics Tester tool. Unlike previous wireline testers, this tool permits testing between probes set as far apart as 8 ft [2.4 m] , a large enough interval to comfortably straddle a stylolite. In such tests recently performed in the Middle East., MDT measurements indicated that stylolites previously assumed to be completely impermeable may in fact be partly conductive to fluid flow.

If stylolites generally impede flow, fractures almost always enhance it. Indeed, some reservoirs, particularly carbonate ones, rely exclusively on fractures to achieve commercial levels of production. 

Before the advent of wireline imaging techniques, detecting fractures was difficult and characterizing anything about them was almost impossible. That bleak outlook changed dramatically with the introduction of the FMI and DSI tools. The recently introduced ARI Azimuthal Resistivity Imager tool also makes an important contribution in fracture detection.

Briefly, all three tools contribute to fracture interpretation, but each alone may not provide a complete picture. On FMI images, open fractures filled with invadingg water-base mud of high conductivity are recognizable as dark and usually fragmented sinusoid traces. With the help of interactive FracView image processing, the interpreter can reliably pinpoint fractures , calculate their dip and azimuth, and estimate spatial density at the borehole. Additional analysis of image resistivity near the fracture can also lead to an estimation of fracture aperture.

With simple models of fracture geometry, the combined log information may provide an effective fracture permeability. This can then be integrated with permebility estimates for the unfractured part of the rock to yield a permeability for the whole rock. In the Rocky Mountains, where a low-porosity carbonate reservoir depends on fractures for production, such a combined permeability has been successfully compared to permeability obtained from drill-stem tests.

There are a few caveats, however, to fracture interpretation using FMI resistivity images. First, the calculated fracture aperture seems to be influenced by the fluid originally flling the fracture- fractures in water zones appear systematically wider than nearby fractures in hydrocarbon zones. It is suspected that invasion fails to remove all hydrocarbon from the walls of the fracture, thereby making the fracture look thinner to electrical imaging techniques. In a depleted carbonate field being exploited for additional oil using horizontal wells, this phenomenon has been put to good use in identifying fractures that are likely to allow water breakthrough. 

 Second, the FMI tool is a relatively shallow measurement , and this limits the tool's ability to distinguish natural fractures that contribute to reservoir performance  from drilling-induced fractures that do not. Certain types of drilling-induced fractures are easily recognized by their geometry - for example, vertical fractures oriented perpendicular to the least horizontal stress and therefore intersecting a vertical borehole over a lenghty interval. Nonvertical drilling induced fractures, however, are harder to distinguish and may be easily confused with the natural variety. Fracture identification in highly deviated and horizontal wells becomes harder still.

The ARI tool provides some added depth of investigation but a poorer along-borehole resolution, and as a result , fewer fractures are detected. However, ARI image processing provides some clue to fracture depth as well as aperture, although neither is unambiguosly determined. The two parameters are genetically linked, so the tool response to a fracture enables an estimate of one of the parameters once a value for the other is taken.

Greater depth of investigation, up to several meters, is provided by the DSI tool that detects open fractures in the same way that it senses a permeable formation - by employing the Stoneley wave to physically pulse mud into and out of the fracture. However, there is a commensurate deterioration in resolution along the borehole axis, to about 1.5 m, showing closely spaced fractures as a single fracture. Like the FMI measurement, the Stoneley wave permits the evaluation of fracture aperture, though again this may actually represent the cumulative apertures of severeal neighboring fractures. Comparisons between fracture aperture estimated from the two techniques have shown good agreement in metamorphic volcanics at a UK waste disposal site.